How AI is transforming the field of change management:

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  1. Data Analysis and Predictions: AI’s ability to analyze vast amounts of data, identify patterns, and make predictions has revolutionized change management [2]. By harnessing AI-powered tools and technologies, organizations can navigate transitions more efficiently, mitigate risks, and maximize the chances of successful outcomes [2]. 
  1. Understanding the Current State and Anticipating Future Challenges: AI provides analytics and insights derived from data gathered from various sources, including internal systems, customer interactions, market trends, and even social media platforms [2]. Through machine learning, natural language processing, and predictive modeling, AI can uncover hidden patterns, identify potential bottlenecks, and forecast the impact of proposed changes accurately and quickly [2]. 
  1. Stakeholder Communication and Collaboration: AI-powered tools and platforms facilitate stakeholder communication and collaboration throughout the change process [2]. Virtual assistants, chatbots, and collaboration platforms equipped with AI capabilities can provide personalized support, answer queries, and disseminate relevant information in real-time, fostering transparency and engagement among employees at all levels [2]. 
  1. Sentiment Analysis: AI-driven sentiment analysis can gauge the emotional pulse of the workforce, enabling leaders to address concerns proactively and tailor their communication strategies to alleviate resistance and build trust [2]. 
  1. Change Management Expertise: Demographic patterns in the data show that expert change management professionals with more than five years of experience use AI in their practice more than novices [1]. Professionals with split responsibilities—as strategy consultants, business leaders, project managers or executive sponsors—also report higher AI usage in their work [1]. 

It is important to note that there are challenges to AI adoption in change management. These include a lack of understanding about how to use AI effectively, inadequate experience with AI, fear of unidentified risks, limited access to tools and resources for applying AI in change management, and concerns about data privacy and security [1]. 

AI is not only often the catalyst behind the need to change, but it is also shifting the way that organizations manage change [4]. With the right communication and integration plan, AI can be used to enhance productivity, performance, and agility at both the organizational and individual levels [4]. 

Sources:  

  1. AI in Change Management: Use Cases, Applications, Implementation and … 
  1. AI in Change Management: Early Findings, Challenges and Opportunities 
  1. 5 ways to think about AI’s role in change management | HR Dive 
  1. AI in Change Management: Use Cases, Applications, Implementation and … 
  1. AI and Change Management | SpringerLink 

What are the Challenges of Having Five Generations in the Workforce? 

According to the U.S. Bureau of Labor Statistics, as of 2021 there are five generations of workers: Traditionalists, also known as The Silent Generation (born before 1946), Baby Boomers (born between 1946 and 1964), Generation X (born between 1965 and 1980), Millennials (born between 1981 and 1996), and Generation Z (born after 1996). 

This generational diversity can bring benefits to organizations, such as increased creativity, innovation, and productivity. However, it can also pose some unique challenges for employers and managers who need to manage and motivate a multigenerational workforce and it could take some time to overcome them. 

Communication Styles 

One of the most obvious challenges of having a multigenerational workforce is the difference in communication styles. Each generation has its own preferences and habits for communicating, both verbally and non-verbally. For example, Traditionalists and Baby Boomers tend to favor formal and face-to-face communication, while Generation X and Millennials prefer informal and digital communication, such as email, text, or social media. Generation Z, the newest generation in the workforce, is even more tech-savvy and accustomed to using multiple platforms and devices for communication. 

Managers need to be aware of the communication preferences of each generation and adapt accordingly. They also need to foster a culture of respect and openness, where employees can express their opinions and feedback without fear of judgment or ridicule. Moreover, managers need to encourage cross-generational communication and collaboration, by creating opportunities for employees to interact and learn from each other, such as mentoring programs, team projects, or social events. 

Technological Adaptation 

Another challenge that stems from having a multigenerational workforce is the difference in technological adaptation. Technology plays a vital role in the modern workplace, as it enables faster, easier, and more efficient processes and outcomes. However, not all generations are equally comfortable with using and learning technology. Younger generations are more adept at embracing and adopting modern technologies, while older generations may struggle or resist them. 

To overcome this challenge, managers need to provide adequate training and support for employees who need to learn new technologies. They also need to explain the benefits and rationale behind the introduction of new technologies, and how they can enhance the work experience and performance of employees. Furthermore, managers need to leverage the strengths and skills of each generation, by assigning tasks and roles that match their technological capabilities and preferences. 

Workplace Expectations 

A third challenge that arises from having a multigenerational workforce is the difference in workplace expectations. Each generation has its own expectations and values regarding work-life balance, job stability, career progression, and organizational loyalty.  

Traditionalists and Baby Boomers tend to value job security, long-term commitment, and hierarchical structures, while Generation X and Millennials tend to value flexibility, autonomy, and horizontal structures. Generation Z, the youngest generation in the workforce, tends to value purpose-driven work, diversity, and social responsibility. 

To overcome this challenge, managers need to understand the expectations and values of each generation and align them with the organizational goals and vision. They also need to provide a variety of rewards and incentives that appeal to different generations, such as financial compensation, recognition, feedback, development opportunities, or work-life balance options. Additionally, managers need to create a culture of trust and transparency, where employees can voice their concerns and expectations and feel valued and respected. 

Motivational Factors 

A fourth challenge that emerges from having a multigenerational workforce is the difference in motivational factors. Each generation has its own sources of motivation and engagement at work, which can influence their performance and satisfaction.  

Traditionalists and Baby Boomers tend to be motivated by duty, respect, and achievement, while Generation X and Millennials tend to be motivated by challenge, feedback, and growth. Generation Z, the most recent generation in the workforce, tends to be motivated by impact, meaning, and social good. 

To overcome this challenge, managers need to identify the motivational factors of each generation and tailor their leadership style accordingly. They also need to provide a clear and compelling vision and mission for the organization and show how each employee contributes to it. Moreover, managers need to empower and involve employees in decision-making and problem-solving, and 

Having five generations in the workforce presents unique challenges for employers and managers. Here are some of the key challenges: 

  • Communication Styles: Each generation has its preferred methods of communication, from traditional face-to-face interactions to digital messaging. Balancing these preferences can be tricky. 
  • Technological Adaptation: Younger generations are typically more comfortable with rapidly changing technology, while older generations may prefer traditional methods. Integrating new technologies in a way that works for everyone requires careful planning. 
  • Workplace Expectations: Different generations have varying expectations regarding work-life balance, job stability, and career progression. Aligning these expectations with organizational goals is a complex task. 
  • Motivational Factors: What motivates employees can differ significantly across generations. For example, some may value job security, while others prioritize flexibility or purpose-driven work. 
  • Resistance to Change: Change can be met with resistance, especially if it affects personal lives. Understanding and managing this resistance is crucial for successful organizational change. 
  • Diversity and Inclusion: Embracing generational diversity and creating an inclusive environment is essential. It involves recognizing and valuing the unique contributions of each age group. 
  • Succession Planning: With a wide age range, succession planning becomes more critical. Organizations must consider all age groups to ensure a smooth transition and continuity. 
  • Learning and Mentoring: There are opportunities for cross-generational learning and mentoring, but facilitating these relationships effectively can be challenging. 
  • Managing Conflict: Different life experiences influence how individuals handle conflict. A multigenerational workforce may require varied approaches to conflict resolution. 
  • Employers who successfully navigate these challenges can harness the strengths of a diverse workforce, leading to increased innovation, productivity, and employee satisfaction [1] [2]. 

Sources: 

1. Generational Differences in the Workplace [Infographic]

2. Multigenerational Workforce: Benefits, Challenges, and 9 Best … – AIHR 

3. Bridging Generational Divides in Your Workplace – Harvard Business Review 

Generative AI: Microsoft Copilot

Microsoft Copilot

About Microsoft Copilot


Microsoft Copilot is a generative artificial intelligence chatbot developed by Microsoft. Launched in February 2023 as Microsoft’s primary replacement for the discontinued Cortana. The service was initially called Bing Chat and was featured as a built-in feature for Microsoft’s search engine Bing and Microsoft’s web browser Edge.

Microsoft Copilot sells the power of its AI to boost “productivity, unlock creativity, and help you understand information better with a simple chat experience.” It coordinates large language models (LLMs), content in Microsoft Graph, and Microsoft 365 productivity apps, such as Word, Excel, PowerPoint, Outlook, Teams, and others.

There are different versions of Copilot:

  • Copilot Free: The basic version that allows you to create original content and answer questions.
  • Copilot Pro: A more robust version for your creativity and productivity that costs $20/month.
  • Copilot for Microsoft 365: This version is optimized for your organization’s Microsoft 365 Business Standard or Business Premium subscription.

Using Microsoft Copilot to generate an image.

Click on Copilot and you will see a place for a prompt. You can experiment with the creative levels.

Enter your prompt, to generate an image

Your image will render

Up to four images will render

Copilot will make some suggestions to change your image

The final output



An AI generated image of Target

How Companies Are Using AI with Their Employees: A Case Study of Target 

Introduction 

Artificial intelligence (AI) is transforming the way businesses operate, from enhancing customer experience to optimizing supply chain management. But AI is not only used for external purposes, but it is also applied internally to improve the productivity, performance, and well-being of employees. In this document, we will explore how companies are using AI with their employees, and examine the case of Target, a leading retailer that has implemented various AI initiatives to empower its workforce. 

How Companies Are Using AI with Their Employees 

According to a report by IBM, 74% of global CEOs say that AI will play a key role in their ability to provide a better work environment for their employees in the next two to three years. Some of the ways that companies are using AI with their employees are: 

  • AI for recruitment and hiring: AI can help companies streamline the hiring process, by automating tasks such as screening resumes, scheduling interviews, and assessing candidates. AI can also help reduce bias and increase diversity in hiring, by using data-driven algorithms and natural language processing to evaluate candidates based on their skills and potential, rather than their demographics or background. 
  • AI for learning and development: AI can help companies provide personalized and adaptive learning experiences for their employees, by analyzing their learning preferences, goals, and progress, and recommending relevant content, courses, and mentors. AI can also help create interactive and engaging learning environments, by using gamification, simulations, and virtual reality to enhance the learning outcomes. 
  • AI for performance and feedback: AI can help companies measure and improve the performance and feedback of their employees, by using data analytics, sentiment analysis, and natural language generation to provide real-time and actionable insights. AI can also help create a culture of continuous feedback and recognition, by using chatbots, voice assistants, and social media platforms to facilitate communication and collaboration among employees and managers. 
  • AI for well-being and engagement: AI can help companies support the well-being and engagement of their employees, by using sensors, wearables, and biometrics to monitor their physical and mental health, and provide personalized interventions and recommendations. AI can also help create a positive and inclusive work environment, by using emotion recognition, natural language understanding, and personality profiling to understand the emotions, needs, and values of employees, and provide them with tailored support and guidance. 

A Case Study of Target 

Target is one of the largest retailers in the United States, with more than 1,900 stores and 350,000 employees (about half the population of Vermont). Target has been investing in AI to enhance its customer experience, such as using computer vision to create smart shelves and using natural language processing to create voice-activated shopping lists. But Target has also been using AI to improve its employee experience, such as using machine learning to create dynamic schedules and using natural language generation to create personalized career paths. Some of the AI initiatives that Target has implemented to empower its employees are: 

  • AI for recruitment and hiring: Target has partnered with HireVue, an AI-powered video interviewing platform, to streamline its hiring process, especially for seasonal workers. Target uses HireVue to screen candidates based on their video responses and rank them based on their fit for the role and the company culture. Target has also partnered with Eightfold, an AI-powered talent intelligence platform, to reduce bias and increase diversity in hiring, by using data-driven algorithms and natural language processing to match candidates with the best opportunities and provide them with feedback and guidance. 
  • AI for learning and development: Target has partnered with Axonify, an AI-powered microlearning platform, to provide personalized and adaptive learning experiences for its employees, especially for frontline workers. Target uses Axonify to deliver bite-sized and gamified learning content, based on the employees’ roles, goals, and knowledge gaps. Target has also partnered with Degreed, an AI-powered learning experience platform, to create interactive and engaging learning environments, by using simulations, virtual reality, and augmented reality to enhance the learning outcomes. 
  • AI for performance and feedback: Target has partnered with Perceptyx, an AI-powered employee survey platform, to measure and improve the performance and feedback of its employees, especially for remote workers. Target uses Perceptyx to collect and analyze employee feedback, using data analytics, sentiment analysis, and natural language generation to provide real-time and actionable insights. Target has also partnered with Workhuman, an AI-powered social recognition platform, to create a culture of continuous feedback and recognition, by using chatbots, voice assistants, and social media platforms to facilitate communication and collaboration among employees and managers. 
  • AI for well-being and engagement: Target has partnered with Thrive Global, an AI-powered well-being platform, to support the well-being and engagement of its employees, especially during the COVID-19 pandemic. Target uses Thrive Global to monitor and improve the physical and mental health of its employees, by using sensors, wearables, and biometrics to provide personalized interventions and recommendations. Target has also partnered with Glint, an AI-powered employee engagement platform, to create a positive and inclusive work environment, by using emotion recognition, natural language understanding, and personality profiling to understand the emotions, needs, and values of employees, and provide them with tailored support and guidance. 

Conclusion 

AI is a tool for enhancing customer experience and a catalyst for improving employee experience. By using AI with their employees, companies can not only increase their efficiency and effectiveness but also their creativity and innovation. Target is a prime example of a company that has leveraged AI to empower its workforce and create a competitive advantage in the retail industry. 

For more information

An AI image of a bunny dressed like a Beefeater

Deep Fakes: A Challenge and an Opportunity

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How technology can create and combat synthetic media 

What are Deep Fakes? 

Deep Fakes are a type of synthetic media that uses artificial intelligence (AI) to manipulate or generate audio, video, or images. They can create realistic-looking content that appears to show people doing or saying things that they never did or said. For example, a Deep Fake video could show a politician making a controversial statement, a celebrity endorsing a product, or a person’s face swapped with another person’s face. 

Below are examples of one with an Arnold Schwarzenegger Deep Fake starring in James Cameron’s Titanic

 

How do Deep Fakes work? 

Deep Fakes are created by using deep learning, a branch of AI that involves training neural networks on large amounts of data. Neural networks are mathematical models that can learn patterns and features from the data and apply them to new inputs. There are different methods to create Deep Fakes, but one of the most common ones is called generative adversarial networks (GANs). 

GANs consist of two neural networks: a generator and a discriminator. The generator tries to create fake content that looks like real content, while the discriminator tries to distinguish between the real and the fake content. The two networks compete, improving their skills over time. The result is fake content that can fool both humans and machines. 

What are the threats of Deep Fakes? 

Deep Fakes pose several threats to individuals, organizations, and society. Some of the potential harms of Deep Fakes are: 

  • Disinformation and propaganda: Deep Fakes can be used to spread false or misleading information, influence public opinion, undermine trust in institutions, and incite violence or conflict. 
  • Identity theft and fraud: Deep Fakes can be used to impersonate someone’s voice, face, or biometric data, and gain access to their personal or financial information, accounts, or devices. 
  • Blackmail and extortion: Deep Fakes can be used to create compromising or embarrassing content that can be used to coerce or threaten someone. 
  • Privacy and consent violation: Deep Fakes can be used to create non-consensual or invasive content that can harm someone’s reputation, dignity, or mental health. 

 An example of how close a Deep Fake can be to the original

The people below were generated by the website www.thispersondoesnotexist.com such images can be used in fake social media accounts.

How are companies dealing with Deep Fakes? 

While Deep Fakes pose a serious challenge, they also offer an opportunity for innovation and collaboration. Many companies are developing tools and solutions to detect, prevent, and mitigate the impact of Deep Fakes. Some of the examples are: 

  • Adobe: Adobe has created a tool called Content Authenticity Initiative (CAI) that aims to provide a secure and verifiable way to attribute the origin and history of digital content. CAI uses cryptography and blockchain to create a tamper-proof record of who created, edited, or shared the content and allows users to verify the authenticity and integrity of the content. 
  • Meta: Meta, formerly known as Facebook, has launched a program called Deep Fake Detection Challenge (DFDC) that aims to accelerate the development of Deep Fake detection technologies. DFDC is a global competition that invites researchers and developers to create and test algorithms that can detect Deep Fakes in videos. DFDC also provides a large and diverse dataset of real and fake videos for training and testing purposes. 
  • Microsoft: Microsoft has developed a tool called Video Authenticator that can analyze videos and images and provide a confidence score of how likely they are to be manipulated. Video Authenticator uses a machine learning model that is trained on a large dataset of real and fake videos, and can detect subtle cues such as fading, blurring, or inconsistent lighting that indicate manipulation. Microsoft also provides a browser extension that can apply the same technology to online content. 
  • X (formerly known as Twitter): X/Twitter has implemented a policy that requires users to label synthetic or manipulated media that are shared on its platform. The policy also states that X/Twitter may remove or flag such media if they are likely to cause harm or confusion. Twitter uses a combination of human review and automated systems to enforce the policy and provide context and warnings to users. 
  • Deeptrace: Deeptrace is a startup that specializes in detecting and analyzing Deep Fakes and other forms of synthetic media. Deeptrace offers a range of products and services, such as Deeptrace API, Deeptrace Dashboard, and Deeptrace Intelligence, that can help clients identify, monitor, and respond to malicious or harmful uses of Deep Fakes. Deeptrace also publishes reports and insights on the trends and developments of synthetic media. 

These are just some of the examples of how companies are tackling the problem of Deep Fakes. There are also other initiatives and collaborations from academia, government, civil society, and media that are working to raise awareness, educate users, and promote ethical and responsible use of synthetic media. 

An AI generated image of a squirrel on a bench on a college campus

Using AI for Education

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A brief overview of some websites and initiatives that assist companies and educational institutions in developing AI use and education policies: 

  1. AI for Education [1]: AI for Education provides guidance and support for crafting practical AI policies. As educators and students increasingly adopt AI, it’s crucial to develop policies and guidelines that ensure ethical use. Whether you need targeted strategic advice or tailored end-to-end support, AI for Education can help you formulate governance frameworks specific to your school or district’s needs. 
  2. TeachAI [2]: TeachAI is an initiative led by Code.org, ETS, the International Society for Technology in Education, Khan Academy, and the World Economic Forum. It unites education and technology leaders to assist governments and education authorities in teaching with and about AI. While not a website specifically for policy development, TeachAI offers valuable resources and insights related to AI in education. 
  3. Office of Educational Technology (OET) [3]: The OET focuses on developing policies and supports for the effective, safe, and fair use of AI-enabled educational technology. Although their primary focus is broader than just policy development, they contribute to the conversation around AI in education. 
  4. Anthology’s AI Policy Framework [4]: Anthology, an edtech firm, released a six-page AI policy framework designed to support higher education institutions interested in developing their own policies around the ethical use of AI. The framework aligns with the AI Risk Management Framework from the National Institute of Standards and Technology. 

Remember to explore these resources further to tailor your policies to your organization’s unique context and requirements. 

Sources:  

  1. AI Policy Development — AI for Education 
  2. Foundational Policy Ideas for AI in Education 
  3. Artificial Intelligence – Office of Educational Technology 
  4. Trying to create a university AI policy? There’s a framework for that … 
An AI generated image of a toolbox

AI Tools that can help a Small Business 

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AI tools that can help improve a small business’s experience with AI. Here are some of them: 

  1. ChatGPT: An AI-powered chatbot [1]. 
  1. Bard: An advanced AI chatbot [1]. 
  1. Kabbage: An AI-driven lending platform [1]. 
  1. Lattice: An AI-powered performance management platform [1]. 
  1. Tara AI: A project management tool with AI features [1]. 
  1. Wordtune: An AI-powered writing assistant [1]. 
  1. Process Street: A workflow automation platform [1]. 
  1. Zoho Zia: An AI assistant for Zoho suite [1]. 
  1. Regie: An AI-powered video analytics platform [1]. 
  1. UiPath: A Robotic Process Automation software [1]. 
  1. AppZen: An AI-based expense report auditing tool [1]. 
  1. SpotIQ: An AI-driven analytics platform [1]. 
  1. HubSpot: A CRM platform with AI features [1]. 
  1. Mindsay: A customer service automation platform [1]. 
  1. Mailchimp: An email marketing platform with AI features [1]. 
  1. GrammarlyGO: An AI-powered writing assistant [1]. 
  1. Starmind: An AI platform for expertise mapping [1]. 
  1. Persado: An AI-powered language generator [1]. 
  1. Gong.io: An AI-powered sales analysis platform [1]. 
  1. EverString: An AI-powered predictive analytics platform [1]. 
  1. MonkeyLearn: A text data analysis tool [1]. 
  1. Invoca: A call tracking and analytics platform [1]. 
  1. Finmark: An AI-based financial planning tool [1]. 
  1. Zeni: An AI-powered finance manager [1]. 
  1. Chata.ai: An AI-powered data interaction tool [1]. 
  1. Hiretual: An AI-powered recruiting platform [1]. 
  1. X0PA AI: An AI-powered solution for recruitment [1]. 
  1. Harver: An AI-based pre-employment assessment software [1]. 
  1. Butterfly.ai: An AI-driven employee feedback tool [1]. 
  1. myInterview: An AI-powered recruiting assistant [1]. 
  1. Beehiive: A cloud-based CRM platform [1]. 
  1. Remini: An AI-powered photo enhancer [1]. 
  1. StarryAI: A text-to-image AI tool [1]. 
  1. Synthesia: An AI-powered video creation tool [1]. 
  1. Writesonic: A text-generating AI tool [1]. 
  1. Kapiche: A text analytics software [1]. 
  1. Optimizely: An AI-driven experimentation and personalization platform [1]. 
  1. Crisp: An AI-powered customer service platform [1]. 
  1. BirdEye: An online reputation management platform [1]. 
  1. Drift: A conversational marketing and sales platform [1]. 
  1. Taskade: A cloud-based project management tool [1]. 
  1. Network AI: An AI-powered networking tool [1]. 

These tools can help in various areas such as customer service, content production, internal communications, customer relationship management (CRM), inventory management, product recommendations, accounting, recruitment and talent sourcing, marketing and sales, and more [2] [3] [4] [5] [6]. It’s important to choose the right tools based on the specific needs and budget of the business [2] [3] [4] [5] [6]. 

Sources:  

  1. AI tools for small business productivity and growth 
  2. The 10 Best AI Tools for Small Businesses and How to Use Them 
  3. 12 Best AI Tools for Small Businesses & Startups (Free & Paid) 
  4. 25 Best Free AI Tools for Business That Truly Help Companies 
  5. AI for Small Business: 14 Tools and 7 Strategies | Birdeye 
  6. 11 AI Tools for Small Businesses (Low Cost, Big Impact!) 
            AI images of a small office in an urban area

            How Small Businesses Are Using AI

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            Small businesses are using AI in a variety of ways to improve their operations, save time, and decrease costs [1]. Here are some key areas where AI is being utilized: 

            1. Cybersecurity and Fraud Management: Over half of business owners use AI for cybersecurity and fraud management [1]. 
            2. Customer Service: Businesses are turning to AI to improve customer service. This includes the use of AI-powered chatbots for instant messaging [1]. 
            3. Content Production: One in three businesses plan to use AI to write website content, while 44% plan to use AI to write content in other languages [1]. 
            4. Internal Communications: Nearly half (46%) of business owners use AI to craft internal communications [1]. 
            5. Customer Relationship Management (CRM): AI is used in CRM to improve customer relationships [1]. 
            6. Inventory Management: AI is also used in inventory management [1]. 
            7. Product Recommendations: AI is leveraged for product recommendations [1]. 
            8. Accounting: AI is used in accounting to automate tedious work [2]. 
            9. Recruitment and Talent Sourcing: AI is used in recruitment and talent sourcing [1]. 
            10. Marketing and Sales: AI is used in marketing and sales to improve content quality and craft prospecting messages [2]. 

                              It’s important to note that while AI can bring many benefits, there are also concerns about over-dependence on technology [1]. Therefore, when choosing AI tools, businesses should consider factors such as budget, specific business needs, ease of implementation, scalability, and ability to integrate with current systems and technology [4]. 

                              Source:  

                              1. How Businesses Are Using Artificial Intelligence In 2024 
                              2. The 10 Best AI Tools for Small Businesses and How to Use Them 
                              3. How Small Businesses Can Use AI Tools – Investopedia 
                              4. Artificial Intelligence for Small Business: The Complete Guide 
                              5. AI for Small Business: 14 Tools and 7 Strategies | Birdeye